Publications associées à Hyperparameter optimization

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Silvestro Micera, Vincent Alexandre Mendez, Leonardo Pollina, Fiorenzo Artoni

The control of robotic prosthetic hands (RPHs) for upper limb amputees is far from optimal. Simultaneous and proportional finger control of a RPH based on EMG signals is still challenging. Based on EMG and kinematics recordings of subjects following a pre- ...

IEEE2021

Progressive Correspondence Pruning by Consensus Learning

Mathieu Salzmann, Chenxu Zhao, Hongwei Li, Feng Zhu, Rui Zhao

Correspondence pruning aims to correctly remove false matches (outliers) from an initial set of putative correspondences. The pruning process is challenging since putative matches are typically extremely unbalanced, largely dominated by outliers, and the r ...

IEEE2021

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Boi Faltings, Claudiu-Cristian Musat, Diego Matteo Antognini

The goal of fairness in classification is to learn a classifier that does not discriminate against groups of individuals based on sensitive attributes, such as race and gender. One approach to designing fair algorithms is to use relaxations of fairness not ...

2021

Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices

David Atienza Alonso, Amir Aminifar, Adriana Arza Valdes, Renato Zanetti

Objective: Cognitive workload monitoring (CWM)can enhance human-machine interaction by supporting task execution assistance considering the operator’s cognitive state. Therefore, we propose a machine learning design methodology and a data processing strate ...

2021

3D Weaving with Curved Ribbons

Mark Pauly, Florin Isvoranu, Tian Chen, Yingying Ren, Samuel Jean Bernard Poincloux, Christopher Brandt

Basket weaving is a traditional craft for creating curved surfaces as an interwoven array of thin, flexible, and initially straight ribbons. The three-dimensional shape of a woven structure emerges through a complex interplay of the elastic bending behavio ...

ASSOC COMPUTING MACHINERY2021

Semantic Perturbations with Normalizing Flows for Improved Generalization

Martin Jaggi, Sebastian Urban Stich, Tatjana Chavdarova

Data augmentation is a widely adopted technique for avoiding overfitting when training deep neural networks. However, this approach requires domain-specific knowledge and is often limited to a fixed set of hard-coded transformations. Recently, several work ...

IEEE2021

Consensus Control for Decentralized Deep Learning

Martin Jaggi, Sebastian Urban Stich, Anastasiia Koloskova, Tao Lin, Lingjing Kong

Decentralized training of deep learning models enables on-device learning over networks, as well as efficient scaling to large compute clusters. Experiments in earlier works reveal that, even in a data-center setup, decentralized training often suffers fro ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

François Fleuret, Martin Jaggi, Thijs Vogels, Jan Frederik Jonas Florian Mai, Prabhu Teja Sivaprasad

The performance of optimizers, particularly in deep learning, depends considerably on their chosen hyperparameter configuration. The efficacy of optimizers is often studied under near-optimal problem-specific hyperparameters, and finding these settings may ...

2020

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Hyperparameter optimization

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Progressive Correspondence Pruning by Consensus Learning

Computationally-guided tuning of ligand sensitivity in a GPCR-based sensor

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices

3D Weaving with Curved Ribbons

Semantic Perturbations with Normalizing Flows for Improved Generalization

Consensus Control for Decentralized Deep Learning

Embedded PWM Predictive Control of DC-DC Power Converters Via Piecewise-Affine Neural Networks

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

Graph Chatbot

Chattez avec Graph Search

Progressive Correspondence Pruning by Consensus Learning

3D Weaving with Curved Ribbons

Embedded PWM Predictive Control of DC-DC Power Converters Via Piecewise-Affine Neural Networks

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Computationally-guided tuning of ligand sensitivity in a GPCR-based sensor

Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices

Consensus Control for Decentralized Deep Learning

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

Semantic Perturbations with Normalizing Flows for Improved Generalization

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings